Jacek Kozak

TL;DR: In this paper, morphological image processing is used for classifying spatial patterns at the pixel level on binary land cover maps, which are classified as perforated, edge, patch, core, and core.

TL;DR: It is noted that chain classification can only be applied when land cover classes are well represented in the overlap area of neighboring Landsat scenes, but as long as this constraint is met, chain classification is a powerful approach for large area land cover classifications, especially in areas of varying training data availability.

TL;DR: In this article, the authors examined the evolution of European land management over the past 200 years with the aim of identifying key episodes of changes in land management, and their underlying technological, institutional and economic drivers.

TL;DR: In this paper, a meta-analysis of 66 publications describing 102 case study locations and quantified the main forest and agricultural changes in the Carpathian region since the 18th century.

TL;DR: In this article, the performance of three regression techniques, namely, partial least squares regression (PLSR), support vector regression (SVR), and multivariate adaptive regression splines (MARS), were compared to identify the best method to assess organic matter (OM) and clay content in the salt-affected soils.